Backtracking Algorithm-based Disassembly Sequence Planning

Abstract

Disassembly sequence planning (DSP) is one of the core research themes of product life cycle design. Effective DSP can reduce product life cycle costs as well as their environmental effects and provides a theoretical future foundation for recycling and improving sustainability performance. The problem with current heuristic artificial intelligence algorithms is that the outcome may have a local extremum; therefore, it may not generate the exact or even the approximate optimum solution. For a specific sequence planning problem, some algorithm parameters need to be adjusted in order to generate a perfect solution. In this study, the objective is to create new DSP by integrating a constraint satisfaction problem (CSP) based on backtracking algorithms. First, the relationship between DSP and the CSP was analysed. Then, the DSP was converted into a CSP based on a disassembly constraint graph (DCG). The solution flowchart of DSP and the CSP-associated algorithms, based on backtracking algorithms, are presented in this article for a dishwasher recycling case study. The outcome of this study shows that the created method can effectively find all of the feasible disassembly sequences as well as the optimum sequence for recycling. Ultimately, these results can be effectively applied to more appliances for future use.